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Little Data: The Key to Solving a $20 Billion Problem?

Previously published on The Fast Mode

Author: Philippe Morin

January 2020


Data is often called ‘the new oil’ by many industry commentators - championed as the key to unlocking new revenue streams for enterprises, or as the way to achieve greater customer retention through highly tailored services. It can also help mobile network operators overcome a US$20 billion-a-year problem: the cost of network outages and service degradations, which is their single largest expense after the cost of the network.

But despite all the hype around big data as the solution to many problems, we are often bogged down in data swamps. Over the past few years, the telecoms industry has been focused on big data, but big data is just that: big and unspecified meta information incapable of revealing the experience of each individual customer, in real time.

To overcome critical business problems like customer churn, operators need highly specific data and prioritized insights that reveal network service degradations in real time - not big data, but “little” data. There is enormous opportunity for operators who successfully get control over the customer experience. Customer retention is enormously important, a tiny improvement is enough to unlock millions in cashflow, this in turn accelerating revenue opportunities for 5G.

We must provide operators with deeper, nuanced and correlated insights to help them ensure a good customer experience, as well as deliver on the promise of connected devices, IoT or smart cities. Little data will serve bottom lines in a big way.

The machines are coming, but how resilient will they be?


There are going to be five times as many “machines” (connected devices) than human subscribers on 5G networks by 2025 - and they will drive 95% of new revenues for operators. Unlike humans, however, new 5G machines, are intolerant to failure. They are diverse and sensitive, fulfilling a number of critical applications.

Operators face the challenge of obtaining better visibility into their network’s performance; if you consider current experiences on mobile devices there are plenty of instances where a user has a full signal and yet suffers a lackluster experience. Often users don’t complain and just shrug off the problems, hopeful the service will restore itself later. But imagine this scenario with mission-critical connected machines instead of humans, machines simply won’t tolerate these failings; automated vehicles or connected devices in homes will “complain” the moment they break down.

Over the next year, MNOs will need to tackle this challenge head-on. There are three core factors that will allow operators to unlock the potential of 5G machines: topology, to give operators the right level of insight about what is occurring across their network; automation, to help operators reduce the costs of managing connected machines and give them the ability to analyze huge data sets; and finally, AI, to help operators assure 5G services for connected machines without needing human oversight.

There will be a degree of trial and error before the industry learns that more resources and attention must be dedicated to safeguarding connected machines, but in the long run, the solutions do exist to deliver fully fledged and reliable performance.

Tech will become the engineer.


There is no bypassing it: fiber infrastructure is the backbone of 5G rollouts. In fact, 100 times more fiber will be required to deploy 5G than is used for 4G today (Corning study, 2019). And yet the industry is now facing a major skills gap: according to Heavy Reading, 82% of mobile operators currently identify the lack of expertise a key blocker in the deployment of fiber and 5G.

As a result, mobile operators are currently outsourcing 44.7% of fiber deployment and management operations to contractors. Outsourcing can deliver results, but the current process can be costly for operators because they still have to check and retest more than 70% of outsourced work - making the whole process very inefficient.

Over the next year, we’ll see a turning point for operators as new technologies “become the engineer”. Rather than wait years to train a new 5G task force of skilled engineers, new technology that uses automation will become a fundamental part of network deployment and optimization. This added agility will allow mobile operators to turn outsourcing into a viable driver for transformation. They’ll still need to test outsourced work, but this will almost all be done automatically via these new “tech engineers,” helping to unclog the process and make transformative 5G technology flow smoothly and efficiently.